The dorsomedial striatum (DMS) is an associative node involved in the initial formation of motor sequences and the adaptation of ongoing actions. During early associative or motor learning tasks, DMS shows a global reduction of activity, eventually refining a subset of active neurons whose number correlates with animal performance. Understanding how this representation emerges is crucial to deciphering the plasticity mechanisms underlying early phases of learning. Here, we propose that local inhibitory interneurons shape early DMS representation and influence task performance. We report that the selective manipulation of somatostatin (SOM)-positive interneurons disrupts DMS activity reorganization and modulates early-learning performance. This effect is cell specific, as manipulation of parvalbumin-positive interneurons has no effect. We also identify the high plasticity of SOM-mediated feedforward inhibition as a critical modulator of striatal projection neuron firing activity. Hence, SOM interneurons are key DMS circuit organizers and set the pace of early learning.

Fragile X syndrome is the most common inherited form of intellectual disability and the leading monogenetic cause of autism. Studies in mouse models of autism spectrum disorders, including the Fmr1 knockout (FX) mouse, suggest that abnormal inhibition in hippocampal circuits contributes to behavioral phenotypes. In FX mice, changes in multiple voltage-gated ion channels occur in excitatory pyramidal neurons of the hippocampus. Whether there are also changes in the intrinsic properties of hippocampal inhibitory interneurons, however, remains largely unknown. We made whole cell current clamp recordings from both fast-spiking (FS) and low threshold spiking (LTS) interneurons in the stratum oriens region of the hippocampus. We found that LTS, but not FS, interneurons in FX mice had lower input resistance and action potential firing compared with the wild type. When we subdivided LTS interneurons into low-threshold high hyperpolarization-activated current (Ih) (LTH) and putative oreins-lacunosum moleculare (OLM) cells (Hewitt et al. Physiol Rep 9: e14848, 2021), we found that it was the LTH subgroup that had significantly lower input resistance in FX mice. The difference in input resistance between wild-type and FX LTH interneurons was absent in the presence of the h-channel blocker ZD7288, suggesting a greater contribution of Ih in FX LTH interneurons. Voltage clamp recordings found that indeed, Ih was significantly higher in FX LTH interneurons compared with wild type. Our results suggest that altered inhibition in the hippocampus of FX mice may be due in part to changes in the intrinsic excitability of LTH inhibitory interneurons.NEW & NOTEWORTHY In this paper, we use physiological and biochemical approaches to investigate the intrinsic excitability of inhibitory interneurons in hippocampal area CA1 of the fragile X mouse. We found that higher Ih lowers the intrinsic excitability of one specific type of interneuron. This study highlights how changes to voltage-gated ion channels in specific neuronal populations may contribute to the altered excitatory/inhibitory balance in fragile X syndrome.

Synaptic inhibition is the mechanistic backbone of a suite of cortical functions, not the least of which are maintaining network stability and modulating neuronal gain. In cortical models with a single inhibitory neuron class, network stabilization and gain control work in opposition to one another - meaning high gain coincides with low stability and vice versa. It is now clear that cortical inhibition is diverse, with molecularly distinguished cell classes having distinct positions within the cortical circuit. We analyze circuit models with pyramidal neurons (E) as well as parvalbumin (PV) and somatostatin (SOM) expressing interneurons. We show how, in E - PV - SOM recurrently connected networks, SOM-mediated modulation can lead to simultaneous increases in neuronal gain and network stability. Our work exposes how the impact of a modulation mediated by SOM neurons depends critically on circuit connectivity and the network state.

Learning involves the association of discrete events in the world to infer causality, likely through a cascade of changes at input- and target-specific synapses. Transient or sustained disinhibition may initiate cortical circuit plasticity important for association learning, but the cellular networks involved have not been well defined. Using recordings in acute brain slices, we show that whisker-dependent sensory association learning drives a durable, target-specific reduction in inhibition from somatostatin (SST)-expressing GABAergic neurons onto pyramidal (Pyr) neurons in superficial but not deep layers of mouse somatosensory cortex. Critically, SST output was not altered when stimuli and rewards were unpaired, indicating that these neurons are sensitive to stimulus-reward contingency. Depression of SST output onto Pyr neurons could be phenocopied by chemogenetic suppression of SST activity outside of the training context. Thus, neocortical SST neuron output can undergo long-lasting modifications to selectively disinhibit superficial layers of sensory neocortex during learning.

Nitrous oxide (N2O) induces rapid and durable antidepressant effects. The cellular and circuit mechanisms mediating this process are not known. Here we find that a single dose of inhaled N2O induces rapid and specific activation of layer V (L5) pyramidal neurons in the cingulate cortex of rodents exposed to chronic stress conditions. N2O-induced L5 activation rescues a stress-associated hypoactivity state, persists following exposure, and is necessary for its antidepressant-like activity. Although NMDA-receptor antagonism is believed to be a primary mechanism of action for N2O, L5 neurons activate even when NMDA-receptor function is attenuated through both pharmacological and genetic approaches. By examining different molecular and circuit targets, we identify N2O-induced inhibition of calcium-sensitive potassium (SK2) channels as a key molecular interaction responsible for driving specific L5 activity along with ensuing antidepressant-like effects. These results suggest that N2O-induced L5 activation is crucial for its fast antidepressant action and this effect involves novel and specific molecular actions in distinct cortical cell types.

Chronic pain affects millions globally, yet no universally effective treatment exists. The primary motor cortex (M1) has been a key target for chronic pain therapies, with electrical stimulation of the M1 (eMCS) showing promise. However, the mechanisms underlying M1-mediated analgesic effects are not fully understood. We investigated the role of the primary somatosensory cortex (S1) in M1-mediated analgesia using a neuropathic pain mouse model. In this model, neuropathic pain is associated with increased spontaneous activity of layer V pyramidal neurons (LV-PNs) in the S1, partly attributed to the reduced activity of somatostatin-expressing inhibitory neurons (SST+ INs), which normally suppress LV-PNs. While manipulation of either LV-PNs or SST+ INs has been shown to alleviate pain, the role of S1 in M1-mediated analgesia has not been identified. Using multichannel silicon probes, we applied eMCS to neuropathic mice and observed significant analgesia. Histological analyses revealed that eMCS activated SST+ INs and suppressed hyperactivity of LV-PNs in the S1, suggesting that eMCS suppresses pain by modulating S1 neuronal circuits, alongside other pain-related regions. Notably, eMCS induced long-lasting analgesia, persisting for at least 2 d poststimulation. These findings implicate S1 as a critical mediator of eMCS-induced analgesia and suggest eMCS as a potential durable therapeutic strategy for chronic pain.

The cortical somatostatin interneuron population includes several diverse cell types, among them the Martinotti cells. Layer-specific differences in connectivity and function between different subtypes of Martinotti cells are becoming apparent, which require contemporary studies to investigate cortical interneurons in a layer and subtype-specific manner. In this study, we investigate the connectivity of a subtype of Chrna2+ layer 5 Martinotti cells in the primary motor cortex, using a monosynaptic retrograde rabies viral tracer. We found direct input from pyramidal cells and local parvalbumin interneurons. In addition, we found long-range direct inputs from the motor thalamus, substantia innominata of the basal forebrain, and globus pallidus. Based on the observed input pattern, we tested and found an increased number of falls in the hanging wire test upon temporary overexcitation of Chrna2+ layer 5 Martinotti cells, suggesting that Chrna2+ Martinotti cells in the motor cortex can interfere with sensorimotor integration. In summary, our study provides novel insights into the connectivity and functional role of Mα2 cells in the M1 forelimb area, highlighting their unique integration of local and long-range inputs critical for sensorimotor processing, which lay the groundwork for further exploration of their role in cortical plasticity and motor learning.

Gamma-frequency oscillations are a hallmark of active information processing and are generated by interactions between excitatory and inhibitory neurons. To examine the contribution of distinct inhibitory interneurons to visually induced gamma oscillations, we recorded from optogenetically identified PV+ (parvalbumin) and Sst+ (somatostatin) interneurons in mouse primary visual cortex (V1). PV and Sst inhibitory interneurons exhibited distinct correlations to gamma oscillations. PV cells were strongly phase locked, while Sst cells were weakly phase locked, except for narrow-waveform Sst cells. PV cells fired at a substantially earlier phase in the gamma cycle (≈6 ms) than Sst cells. PV cells fired shortly after the onset of tightly synchronized burst events in excitatory cells, while Sst interneurons fired after subsequent burst spikes or single spikes. These findings indicate a main role of PV interneurons in synchronizing network activity and suggest that PV and Sst interneurons control the excitability of somatic and dendritic neural compartments with precise time delays coordinated by gamma oscillations.

Somatostatin-expressing (SST) neurons are a major class of electrophysiologically and morphologically distinct inhibitory cells in the mammalian neocortex. Transcriptomic data suggest that this class can be divided into multiple subtypes that are correlated with morpho-electric properties. At the same time, availability of transgenic tools to identify and record from SST neurons in awake, behaving mice has stimulated insights about their response properties and computational function. Neocortical SST neurons are regulated by sleep and arousal, attention, and novelty detection, and show marked response plasticity during learning. Recent studies suggest that subtype-specific analysis of SST neurons may be critical for understanding their complex roles in cortical function. In this review, we discuss and synthesize recent advances in understanding the diversity, circuit integration, and functional properties of this important group of GABAergic neurons.

Learning motor skills requires plasticity in the primary motor cortex (M1). But the capacity for cortical circuit plasticity varies over developmental age in sensory cortex. This study assesses the normal developmental trajectory of motor learning to assess how aptitude might vary with age. We trained mice of both sexes to run on a custom accelerating rotarod at ages from postnatal day (P) 20 to P120, tracking paw position and quantifying time to fall and changes in gait pattern. While animals of all ages were able to perform better after five training sessions, performance improved most rapidly on the first training day for mice between ages P30-60, suggesting an age with heightened plasticity. Learning this task required M1, because pharmacological inactivation of M1 prevented improvement in task performance. Paw position and gait patterns changed with learning, though differently between age groups. Successful mice learned to shift their gait from hopping to walking. Notably, this shift in gait happened earlier in the trial for forelimbs in comparison to hindlimbs. Thus, motor plasticity might more readily occur in forelimbs. Changes in gait and other kinematic parameters are an additional learning metric beyond time to fall, offering insight into how mice improve performance. Overall, these results suggest mouse motor learning has a developmental trajectory.

The medial frontal cortex (mFC) and locus ceruleus (LC) are two brain areas that have been implicated in a range of cognitive phenomena, such as attention, memory, and decision-making. Regulators of these brain regions at the molecular level are not well understood but might help to elucidate underlying mechanisms of disorders that present with deficits in these cognitive domains. To probe this, we used chemogenetic stimulation of neurons in the LC with axonal projections to the prelimbic subregion (PrL) of the mFC and subsequent bulk RNA sequencing from the mouse PrL. We found that stimulation of this circuit caused an increase in transcription of a host of genes, including the Apoe gene. To investigate cell type-specific expression of Apoe in the PrL, we used a dual-virus approach to express either the excitatory DREADD receptor hM3Dq in LC neurons with projections to the PrL or a control virus and found that increases in Apoe expression in the PrL following depolarization of LC inputs is enriched in GABAergic neurons in a sex-dependent manner. The results of these experiments yield insights into how Apoe expression affects function in a cortical microcircuit that is important for attention, memory, and decision-making and point to interneuron-specific expression of Apoe as a potential biomarker for circuit function in disorders such as attention-deficit hyperactivity disorder, schizophrenia, and Alzheimer's disease.

Somatostatin (SST)-expressing inhibitory neurons are a major class of neocortical γ-amino butyric acid (GABA) neurons, where morphological, electrophysiological, and transcriptomic analyses indicate more than a dozen different subtypes. However, whether this diversity is related to specific roles in cortical computations and plasticity remains unclear. Here we identify learning-dependent, subtype-specific plasticity in layer 2/3 SST neurons of the mouse somatosensory cortex. Martinotti-type, SST neurons expressing calbindin-2 show a selective decrease in excitatory synaptic input and stimulus-evoked calcium responses as mice learn a stimulus-reward association. Using these insights, we develop a label-free classifier using basal activity from in vivo imaging that accurately predicts learning-associated response plasticity. Our data indicate that molecularly-defined SST neuron subtypes play specific and highly-regulated roles in sensory information processing and learning.

It is unclear how early neuronal deficits occur in tauopathies, if these are associated with changes in neuronal network activity, and if they can be alleviated with therapies.

To address this, we performed in vivo two-photon Ca2+ imaging in tauopathy mice at 6 versus 12 months, compared to controls, and treated the younger animals with a tau antibody.

Neuronal function was impaired at 6 months but did not deteriorate further at 12 months, presumably because cortical tau burden was comparable at these ages. At 6 months, neurons were mostly hypoactive, with enhanced neuronal synchrony, and had dysregulated responses to stimulus. Ex vivo, electrophysiology revealed altered synaptic transmission and enhanced excitability of motor cortical neurons, which likely explains the altered network activity. Acute tau antibody treatment reduced pathological tau and gliosis and partially restored neuronal function.

Tauopathies are associated with early neuronal deficits that can be attenuated with tau antibody therapy.

Neuronal hypofunction in awake and behaving mice in early stages of tauopathy. Altered network activity disrupted local circuitry engagement in tauopathy mice. Enhanced neuronal excitability and altered synaptic transmission in tauopathy mice. Tau antibody acutely reduced soluble phospho-tau and improved neuronal function.

Short-term plasticity is an important feature in the brain for shaping neural dynamics and for information processing. Short-term plasticity is known to depend on many factors including brain region, cortical layer, and cell type. Here we focus on vasoactive-intestinal peptide (VIP) interneurons (INs). VIP INs play a key disinhibitory role in cortical circuits by inhibiting other IN types, including Martinotti cells (MCs) and basket cells (BCs). Despite this prominent role, short-term plasticity at synapses to and from VIP INs is not well described. In this study, we therefore characterized the short-term plasticity at inputs and outputs of genetically targeted VIP INs in mouse motor cortex. To explore inhibitory to inhibitory (I → I) short-term plasticity at layer 2/3 (L2/3) VIP IN outputs onto L5 MCs and BCs, we relied on a combination of whole-cell recording, 2-photon microscopy, and optogenetics, which revealed that VIP IN→MC/BC synapses were consistently short-term depressing. To explore excitatory (E) → I short-term plasticity at inputs to VIP INs, we used extracellular stimulation. Surprisingly, unlike VIP IN outputs, E → VIP IN synapses exhibited heterogeneous short-term dynamics, which we attributed to the target VIP IN cell rather than the input. Computational modeling furthermore linked the diversity in short-term dynamics at VIP IN inputs to a wide variability in probability of release. Taken together, our findings highlight how short-term plasticity at VIP IN inputs and outputs is specific to synapse type. We propose that the broad diversity in short-term plasticity of VIP IN inputs forms a basis to code for a broad range of contrasting signal dynamics.

One key function of the brain is to control our body's movements, allowing us to interact with the world around us. Yet, many motor behaviors are not innate but require learning through repeated practice. Among the brain's motor regions, the cortico-basal ganglia circuit is particularly crucial for acquiring and executing motor skills, and neuronal activity in these regions is directly linked to movement parameters. Cell-type-specific adaptations of activity patterns and synaptic connectivity support the learning of new motor skills. Functionally, neuronal activity sequences become structured and associated with learned movements. On the synaptic level, specific connections become potentiated during learning through mechanisms such as long-term synaptic plasticity and dendritic spine dynamics, which are thought to mediate functional circuit plasticity. These synaptic and circuit adaptations within the cortico-basal ganglia circuitry are thus critical for motor skill acquisition, and disruptions in this plasticity can contribute to movement disorders.

Deficits in attention are common across a range of neuropsychiatric disorders. A multitude of brain regions, including the frontal cortex (FC) and locus coeruleus (LC), have been implicated in attention. Regulators of these brain regions at the molecular level are not well understood, but might elucidate underlying mechanisms of disorders with attentional deficits. To probe this, we used chemogenetic stimulation of neurons in the LC with axonal projections to the FC, and subsequent bulk RNA-sequencing from the mouse FC. We found that stimulation of this circuit caused an increase in transcription of the Apoe gene. To investigate cell type-specific expression of Apoe in the FC, we used a dual-virus approach to express either the excitatory DREADD receptor hM3Dq in LC neurons with projections to the FC, or a control virus, and found that increases in Apoe expression in the FC following depolarization of LC inputs is enriched in GABAergic neurons in a sex-dependent manner. The results of these experiments yield insights into how Apoe expression affects function in cortical microcircuits that are important for attention-guided behavior, and point to interneuron-specific expression of Apoe as a potential target for the amelioration of attention symptoms in disorders such as attention-deficit hyperactivity disorder (ADHD), schizophrenia, and Alzheimer's disease (AD).

Microglia sense the changes in their environment. How microglia actively translate these changes into suitable cues to adapt brain physiology is unknown. We reveal an activity-dependent regulation of cortical inhibitory synapses by microglia, driven by purinergic signaling acting on P2RX7 and mediated by microglia-derived TNFα. We demonstrate that sleep induces microglia-dependent synaptic enrichment of GABAARs in a manner dependent on microglial TNFα and P2RX7. We further show that microglia-specific depletion of TNFα alters slow waves during NREM sleep and blunt memory consolidation in sleep-dependent learning tasks. Together, our results reveal that microglia orchestrate sleep-intrinsic plasticity of synaptic GABAARs, sculpt sleep slow waves, and support memory consolidation.

We previously reported altered neuronal Ca 2+ dynamics in the motor cortex of 12-month-old JNPL3 tauopathy mice during quiet wakefulness or forced running, with a tau antibody treatment significantly restoring the neuronal Ca 2+ activity profile and decreasing pathological tau in these mice 1 . Whether neuronal functional deficits occur at an early stage of tauopathy and if tau antibody treatment is effective in younger tauopathy mice needed further investigation. In addition, neuronal network activity and neuronal firing patterns have not been well studied in behaving tauopathy models. In this study, we first performed in vivo two-photon Ca 2+ imaging in JNPL3 mice in their early stage of tauopathy at 6 months of age, compared to 12 month old mice and age-matched wild-type controls to evaluate neuronal functional deficits. At the animal level, frequency of neuronal Ca 2+ transients decreased only in 6 month old tauopathy mice compared to controls, and only when animals were running on a treadmill. The amplitude of neuronal transients decreased in tauopathy mice compared to controls under resting and running conditions in both age groups. Total neuronal activity decreased only in 6 month old tauopathy mice compared to controls under resting and running conditions. Within either tauopathy or wild-type group, only total activity decreased in older wild-type animals. The tauopathy mice at different ages did not differ in neuronal Ca 2+ transient frequency, amplitude or total activity. In summary, neuronal function did significantly attenuate at an early age in tauopathy mice compared to controls but interestingly did not deteriorate between 6 and 12 months of age. A more detailed populational analysis of the pattern of Ca 2+ activity at the neuronal level in the 6 month old cohort confirmed neuronal hypoactivity in layer 2/3 of primary motor cortex, compared to wild-type controls, when animals were either resting or running on a treadmill. Despite reduced activity, neuronal Ca 2+ profiles exhibited enhanced synchrony and dysregulated responses to running stimulus. Further ex vivo electrophysiological recordings revealed reduction of spontaneous excitatory synaptic transmission onto and in pyramidal neurons and enhanced excitability of inhibitory neurons in motor cortex, which were likely responsible for altered neuronal network activity in this region. Lastly, tau antibody treatment reduced pathological tau and gliosis partially restored the neuronal Ca 2+ activity deficits but failed to rescue altered network changes. Taken together, substantial neuronal and network dysfunction occurred in the early stage of tauopathy that was partially alleviated with acute tau antibody treatment, which highlights the importance of functional assessment when evaluating the therapeutic potential of tau antibodies.

Layer 2/3 motor cortical neurons exhibited hypofunction in awake and behaving mice at the early stage of tauopathy.Altered neuronal network activity disrupted local circuitry engagement in tauopathy mice during treadmill running.Layer 2/3 motor cortical neurons in tauopathy mice exhibited enhanced neuronal excitability and altered excitatory synaptic transmissions.Acute tau antibody treatment reduced pathological tau and gliosis, and partially restored neuronal hypofunction profiles but not network dysfunction.

Training rodents in a particularly difficult olfactory-discrimination (OD) task results in the acquisition of the ability to perform the task well, termed 'rule learning'. In addition to enhanced intrinsic excitability and synaptic excitation in piriform cortex pyramidal neurons, rule learning results in increased synaptic inhibition across the whole cortical network to the point where it precisely maintains the balance between inhibition and excitation. The mechanism underlying such precise inhibitory enhancement remains to be explored. Here, we use brain slices from transgenic mice (VGAT-ChR2-EYFP), enabling optogenetic stimulation of single GABAergic neurons and recordings of unitary synaptic events in pyramidal neurons. Quantal analysis revealed that learning-induced enhanced inhibition is mediated by increased quantal size of the evoked inhibitory events. Next, we examined the plasticity of synaptic inhibition induced by long-lasting, intrinsically evoked spike firing in post-synaptic neurons. Repetitive depolarizing current pulses from depolarized (-70 mV) or hyperpolarized (-90 mV) membrane potentials induced long-term depression (LTD) and long-term potentiation (LTP) of synaptic inhibition, respectively. We found a profound bidirectional increase in the ability to induce both LTD, mediated by L-type calcium channels, and LTP, mediated by R-type calcium channels after rule learning. Blocking the GABAB receptor reversed the effect of intrinsic stimulation at -90 mV from LTP to LTD. We suggest that learning greatly enhances the ability to modify the strength of synaptic inhibition of principal neurons in both directions. Such plasticity of synaptic plasticity allows fine-tuning of inhibition on each particular neuron, thereby stabilizing the network while maintaining the memory of the rule. KEY POINTS: Olfactory discrimination rule learning results in long-lasting enhancement of synaptic inhibition on piriform cortex pyramidal neurons. Quantal analysis of unitary inhibitory synaptic events, evoked by optogenetic minimal stimulation, revealed that enhanced synaptic inhibition is mediated by increased quantal size. Surprisingly, metaplasticity of synaptic inhibition, induced by intrinsically evoked repetitive spike firing, is increased bidirectionally. The susceptibility to both long-term depression (LTD) and long-term potentiation (LTP) of inhibition is enhanced after learning. LTD of synaptic inhibition is mediated by L-type calcium channels and LTP by R-type calcium channels. LTP is also dependent on activation of GABAB receptors. We suggest that learning-induced changes in the metaplasticity of synaptic inhibition enable the fine-tuning of inhibition on each particular neuron, thereby stabilizing the network while maintaining the memory of the rule.

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.

Many studies indicate a broad role of various classes of GABAergic interneurons in the processes related to learning. However, little is known about how the learning process affects intrinsic excitability of specific classes of interneurons in the neocortex. To determine this, we employed a simple model of conditional learning in mice where vibrissae stimulation was used as a conditioned stimulus and a tail shock as an unconditioned one. In vitro whole-cell patch-clamp recordings showed an increase in intrinsic excitability of low-threshold spiking somatostatin-expressing interneurons (SST-INs) in layer 4 (L4) of the somatosensory (barrel) cortex after the conditioning paradigm. In contrast, pseudoconditioning reduced intrinsic excitability of SST-LTS, parvalbumin-expressing interneurons (PV-INs), and vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) with accommodating pattern in L4 of the barrel cortex. In general, increased intrinsic excitability was accompanied by narrowing of action potentials (APs), whereas decreased intrinsic excitability coincided with AP broadening. Altogether, these results show that both conditioning and pseudoconditioning lead to plastic changes in intrinsic excitability of GABAergic interneurons in a cell-specific manner. In this way, changes in intrinsic excitability can be perceived as a common mechanism of learning-induced plasticity in the GABAergic system.

Among the central features of Alzheimer's disease (AD) progression are altered levels of the neuropeptide somatostatin (SST), and the colocalisation of SST-positive interneurons (SST-INs) with amyloid-β plaques, leading to cell death. In this theoretical review, I propose a molecular model for the pathogenesis of AD based on SST-IN hypofunction and hyperactivity. Namely, hypofunctional and hyperactive SST-INs struggle to control hyperactivity in medial regions in early stages, leading to axonal Aβ production through excessive presynaptic GABAB inhibition, GABAB1a/APP complex downregulation and internalisation. Concomitantly, excessive SST-14 release accumulates near SST-INs in the form of amyloids, which bind to Aβ to form toxic mixed oligomers. This leads to differential SST-IN death through excitotoxicity, further disinhibition, SST deficits, and increased Aβ release, fibrillation and plaque formation. Aβ plaques, hyperactive networks and SST-IN distributions thereby tightly overlap in the brain. Conversely, chronic stimulation of postsynaptic SST2/4 on gulutamatergic neurons by hyperactive SST-INs promotes intense Mitogen-Activated Protein Kinase (MAPK) p38 activity, leading to somatodendritic p-tau staining and apoptosis/neurodegeneration - in agreement with a near complete overlap between p38 and neurofibrillary tangles. This model is suitable to explain some of the principal risk factors and markers of AD progression, including mitochondrial dysfunction, APOE4 genotype, sex-dependent vulnerability, overactive glial cells, dystrophic neurites, synaptic/spine losses, inter alia. Finally, the model can also shed light on qualitative aspects of AD neuropsychology, especially within the domains of spatial and declarative (episodic, semantic) memory, under an overlying pattern of contextual indiscrimination, ensemble instability, interference and generalisation.

Alzheimer's disease (AD) is characterised by age-related cognitive decline. Brain accumulation of amyloid-β plaques and tau tangles is required for a neuropathological AD diagnosis, yet up to one-third of AD-pathology positive community-dwelling elderly adults experience no symptoms of cognitive decline during life. Conversely, some exhibit chronic cognitive impairment in absence of measurable neuropathology, prompting interest into cognitive resilience-retained cognition despite significant neuropathology-and cognitive frailty-impaired cognition despite low neuropathology. Synapse loss is widespread within the AD-dementia, but not AD-resilient, brain. Recent evidence points towards critical roles for synaptic proteins, such as neurosecretory VGF, in cognitive resilience. However, VGF and related proteins often signal as peptide derivatives. Here, nontryptic peptidomic mass spectrometry was performed on 102 post-mortem cortical samples from individuals across cognitive and neuropathological spectra. Neuropeptide signalling proteoforms derived from VGF, somatostatin (SST) and protachykinin-1 (TAC1) showed higher abundance in AD-resilient than AD-dementia brain, whereas signalling proteoforms of cholecystokinin (CCK) and chromogranin (CHG) A/B and multiple cytoskeletal molecules were enriched in frail vs control brain. Integrating our data with publicly available single nuclear RNA sequencing (snRNA-seq) showed enrichment of cognition-related genes in defined cell-types with established links to cognitive resilience, including SST interneurons and excitatory intratelencephalic cells.

The hippocampus is the brain's center for episodic memories. Its subregions, the dentate gyrus and CA1-3, are differentially involved in memory encoding and recall. Hippocampal principal cells represent episodic features like movement, space, and context, but less is known about GABAergic interneurons. Here, we performed two-photon calcium imaging of parvalbumin- and somatostatin-expressing interneurons in the dentate gyrus and CA1-3 of male mice exploring virtual environments. Parvalbumin-interneurons increased activity with running-speed and reduced it in novel environments. Somatostatin-interneurons in CA1-3 behaved similar to parvalbumin-expressing cells, but their dentate gyrus counterparts increased activity during rest and in novel environments. Congruently, chemogenetic silencing of dentate parvalbumin-interneurons had prominent effects in familiar contexts, while silencing somatostatin-expressing cells increased similarity of granule cell representations between novel and familiar environments. Our data indicate unique roles for parvalbumin- and somatostatin-positive interneurons in the dentate gyrus that are distinct from those in CA1-3 and may support routing of novel information.

Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.

Brain computation relies on the neural networks. Neurons extend the neurites such as dendrites and axons, and the contacts of these neurites that form chemical synapses are the biological basis of signal transmissions in the central nervous system. Individual neuronal outputs can influence the other neurons within the range of the axonal spread, while the activities of single neurons can be affected by the afferents in their somatodendritic fields. The morphological profile, therefore, binds the functional role each neuron can play. In addition, synaptic connectivity among neurons displays preference based on the characteristics of presynaptic and postsynaptic neurons. Here, the author reviews the "spatial" and "temporal" connection selectivity in the neocortex. The histological description of the neocortical circuitry depends primarily on the classification of cell types, and the development of gene engineering techniques allows the cell type-specific visualization of dendrites and axons as well as somata. Using genetic labeling of particular cell populations combined with immunohistochemistry and imaging at a subcellular spatial resolution, we revealed the "spatial selectivity" of cortical wirings in which synapses are non-uniformly distributed on the subcellular somatodendritic domains in a presynaptic cell type-specific manner. In addition, cortical synaptic dynamics in learning exhibit presynaptic cell type-dependent "temporal selectivity": corticocortical synapses appear only transiently during the learning phase, while learning-induced new thalamocortical synapses persist, indicating that distinct circuits may supervise learning-specific ephemeral synapse and memory-specific immortal synapse formation. The selectivity of spatial configuration and temporal reconfiguration in the neural circuitry may govern diverse functions in the neocortex.

The meta-reinforcement learning (meta-RL) framework, which involves RL over multiple timescales, has been successful in training deep RL models that generalize to new environments. It has been hypothesized that the prefrontal cortex may mediate meta-RL in the brain, but the evidence is scarce. Here we show that the orbitofrontal cortex (OFC) mediates meta-RL. We trained mice and deep RL models on a probabilistic reversal learning task across sessions during which they improved their trial-by-trial RL policy through meta-learning. Ca2+/calmodulin-dependent protein kinase II-dependent synaptic plasticity in OFC was necessary for this meta-learning but not for the within-session trial-by-trial RL in experts. After meta-learning, OFC activity robustly encoded value signals, and OFC inactivation impaired the RL behaviors. Longitudinal tracking of OFC activity revealed that meta-learning gradually shapes population value coding to guide the ongoing behavioral policy. Our results indicate that two distinct RL algorithms with distinct neural mechanisms and timescales coexist in OFC to support adaptive decision-making.

A substantial proportion of raphe neurons are glutamatergic. However, little is known about how these glutamatergic neurons modulate the forebrain. We investigated how glutamatergic median raphe nucleus (MRN) input modulates the medial prefrontal cortex (mPFC), a critical component of fear circuitry. We show that vesicular glutamate transporter 3 (VGLUT3)-expressing MRN neurons activate VGLUT3- and somatostatin-expressing neurons in the mPFC. Consistent with this modulation of mPFC GABAergic neurons, activation of MRN (VGLUT3) neurons enhances GABAergic transmission in mPFC pyramidal neurons and attenuates fear memory in female but not male mice. Serotonin plays a key role in MRN (VGLUT3) neuron-mediated GABAergic plasticity in the mPFC. In agreement with these female-specific effects, we observed sex differences in glutamatergic transmission onto MRN (VGLUT3) neurons and in mPFC (VGLUT3) neuron-mediated dual release of glutamate and GABA. Our results demonstrate a cell type-specific modulation of the mPFC by MRN (VGLUT3) neurons and reveal a sex-specific role of this neuromodulation in mPFC synaptic plasticity.

Motor learning is crucial for the survival of many animals. Acquiring a new motor skill involves complex alterations in both local neural circuits in many brain regions and long-range connections between them. Such changes can be observed anatomically and functionally. The primary motor cortex (M1) integrates information from diverse brain regions and plays a pivotal role in the acquisition and refinement of new motor skills. In this review, we discuss how motor learning affects the M1 at synaptic, cellular, and circuit levels. Wherever applicable, we attempt to relate and compare findings in humans, non-human primates, and rodents. Understanding the underlying principles shared by different species will deepen our understanding of the neurobiological and computational basis of motor learning.

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.

The current understanding of the neuromodulatory role of the median raphe nucleus (MRN) is primarily based on its putative serotonergic output. However, a significant proportion of raphe neurons are glutamatergic. The present study investigated how glutamatergic MRN input modulates the medial prefrontal cortex (mPFC), a critical component of the fear circuitry. Our studies show that VGLUT3-expressing MRN neurons modulate VGLUT3- and somatostatin-expressing neurons in the mPFC. Consistent with this modulation of mPFC GABAergic neurons, activation of MRN (VGLUT3) neurons suppresses mPFC pyramidal neuron activity and attenuates fear memory in female but not male mice. In agreement with these female-specific effects, we observed sex differences in glutamatergic transmission onto MRN (VGLUT3) neurons and mPFC (VGLUT3) neuron-mediated dual release of glutamate and GABA. Thus, our results demonstrate a cell type-specific modulation of the mPFC by MRN (VGLUT3) neurons and reveal a sex-specific role of this neuromodulation in mPFC synaptic plasticity and fear memory.

During learning, multi-dimensional inputs are integrated within the sensory cortices. However, the strategies by which the sensory cortex employs to achieve learning remains poorly understood. We studied the sensory cortical neuronal coding of trace eyeblink conditioning (TEC) in head-fixed, freely running mice, where whisker deflection was used as a conditioned stimulus (CS) and an air puff to the cornea delivered after an interval was used as unconditioned stimulus (US). After training, mice learned the task with a set of stereotypical behavioral changes, most prominent ones include prolonged closure of eyelids, and increased reverse running between CS and US onset. The local blockade of the primary somatosensory cortex (S1) activities with muscimol abolished the behavior learning suggesting that S1 is required for the TEC. In naive animals, based on the response properties to the CS and US, identities of the small proportion (~20%) of responsive primary neurons (PNs) were divided into two subtypes: CR (i.e. CS-responsive) and UR neurons (i.e. US-responsive). After animals learned the task, identity of CR and UR neurons changed: while the CR neurons are less responsive to CS, UR neurons gain responsiveness to CS, a new phenomenon we defined as 'learning induced neuronal identity switch (LINIS)'. To explore the potential mechanisms underlying LINIS, we found that systemic and local (i.e. in S1) administration of the nicotinic receptor antagonist during TEC training blocked the LINIS, and concomitantly disrupted the behavior learning. Additionally, we monitored responses of two types of cortical interneurons (INs) and observed that the responses of the somatostatin-expressing (SST), but not parvalbumin-expressing (PV) INs are negatively correlated with the learning performance, suggesting that SST-INs contribute to the LINIS. Thus, we conclude that L2/3 PNs in S1 encode perceptual learning by LINIS like mechanisms, and cholinergic pathways and cortical SST interneurons are involved in the formation of LINIS.

To determine what actions to perform in each context, animals must learn how to execute motor programs in response to sensory cues. In rodents, the interface between sensory processing and motor planning occurs in the secondary motor cortex (M2). Here, we investigate dynamics in vasointestinal peptide (VIP) and somatostatin (SST) interneurons in M2 during acquisition of a cue-based, reach-to-grasp (RTG) task in mice. We observe the emergence of preparatory activity consisting of sensory responses and ramping activation in a subset of VIP interneurons during motor learning. We show that preparatory and movement activities in VIP neurons exhibit compartmentalized dynamics, with principal component 1 (PC1) and PC2 reflecting primarily movement and preparatory activity, respectively. In contrast, we observe later and more synchronous activation of SST neurons during the movement epoch with learning. Our results reveal how VIP population dynamics might support sensorimotor learning and compartmentalization of sensory processing and movement execution.

Neocortical spiking dynamics control aspects of behavior, yet how these dynamics emerge during motor learning remains elusive. Activity-dependent synaptic plasticity is likely a key mechanism, as it reconfigures network architectures that govern neural dynamics. Here, we examined how the mouse premotor cortex acquires its well-characterized neural dynamics that control movement timing, specifically lick timing. To probe the role of synaptic plasticity, we have genetically manipulated proteins essential for major forms of synaptic plasticity, Ca2+/calmodulin-dependent protein kinase II (CaMKII) and Cofilin, in a region and cell-type-specific manner. Transient inactivation of CaMKII in the premotor cortex blocked learning of new lick timing without affecting the execution of learned action or ongoing spiking activity. Furthermore, among the major glutamatergic neurons in the premotor cortex, CaMKII and Cofilin activity in pyramidal tract (PT) neurons, but not intratelencephalic (IT) neurons, is necessary for learning. High-density electrophysiology in the premotor cortex uncovered that neural dynamics anticipating licks are progressively shaped during learning, which explains the change in lick timing. Such reconfiguration in behaviorally relevant dynamics is impeded by CaMKII manipulation in PT neurons. Altogether, the activity of plasticity-related proteins in PT neurons plays a central role in sculpting neocortical dynamics to learn new behavior.

Inhibitory interneurons play a crucial role in proper development and function of the mammalian cerebral cortex. Of the different inhibitory subclasses, dendritic-targeting, somatostatin-containing (SOM) interneurons may be the most diverse. Earlier studies used GFP-expressing and recombinase-expressing mouse lines to characterize genetically defined subtypes of SOM interneurons by morphologic, electrophysiological, and neurochemical properties. More recently, large-scale studies classified SOM interneurons into 13 morpho-electric transcriptomic (MET) types. It remains unclear, however, how these various classification schemes relate to each other, and experimental access to MET types has been limited by the scarcity of specific mouse driver lines. To address these issues, we crossed Flp and Cre driver lines with a dual-color intersectional reporter, allowing experimental access to several combinatorially defined SOM subsets. Brains from adult mice of both sexes were retrogradely dye labeled from the pial surface to identify layer 1-projecting neurons and immunostained against several marker proteins, revealing correlations between genetic label, axonal target, and marker protein expression in the same neurons. Lastly, using whole-cell recordings ex vivo, we analyzed and compared electrophysiological properties between different intersectional subsets. We identified two layer 1-targeting subtypes with nonoverlapping marker protein expression and electrophysiological properties, which, together with a previously characterized layer 4-targeting subtype, account for >50% of all layer 5 SOM cells and >40% of all SOM cells, and appear to map onto 5 of the 13 MET types. Genetic access to these subtypes will allow researchers to determine their synaptic inputs and outputs and uncover their roles in cortical computations and animal behavior.

Genetically defined subgroups of inhibitory interneurons are thought to play distinct roles in learning, but heterogeneity within these subgroups has limited our understanding of the scope and nature of their specific contributions. Here we reveal that the chandelier cell (ChC), an interneuron type that specializes in inhibiting the axon-initial segment (AIS) of pyramidal neurons, establishes cortical microcircuits for organizing neural coding through selective axo-axonic synaptic plasticity. We found that organized motor control is mediated by enhanced population coding of direction-tuned premotor neurons, with tuning refined through suppression of irrelevant neuronal activity. ChCs contribute to learning-dependent refinements by providing selective inhibitory control over individual pyramidal neurons rather than global suppression. Quantitative analysis of structural plasticity across axo-axonic synapses revealed that ChCs redistributed inhibitory weights to individual pyramidal neurons during learning. These results demonstrate an adaptive logic of the inhibitory circuit motif responsible for organizing distributed neural representations. Thus, ChCs permit efficient cortical computation in a targeted cell-specific manner.

Somatostatin interneurons are the earliest born population of cortical inhibitory cells. They are crucial to support normal brain development and function; however, the mechanisms underlying their integration into nascent cortical circuitry are not well understood. In this study, we begin by demonstrating that the maturation of somatostatin interneurons in mouse somatosensory cortex is activity dependent. We then investigated the relationship between activity, alternative splicing, and synapse formation within this population. Specifically, we discovered that the Nova family of RNA-binding proteins are activity-dependent and are essential for the maturation of somatostatin interneurons, as well as their afferent and efferent connectivity. Within this population, Nova2 preferentially mediates the alternative splicing of genes required for axonal formation and synaptic function independently from its effect on gene expression. Hence, our work demonstrates that the Nova family of proteins through alternative splicing are centrally involved in coupling developmental neuronal activity to cortical circuit formation.

A key driver of mammalian intelligence is the ability to represent incoming sensory information across multiple abstraction levels. For example, in the visual ventral stream, incoming signals are first represented as low-level edge filters and then transformed into high-level object representations. Similar hierarchical structures routinely emerge in artificial neural networks (ANNs) trained for object recognition tasks, suggesting that similar structures may underlie biological neural networks. However, the classical ANN training algorithm, backpropagation, is considered biologically implausible, and thus alternative biologically plausible training methods have been developed such as Equilibrium Propagation, Deep Feedback Control, Supervised Predictive Coding, and Dendritic Error Backpropagation. Several of those models propose that local errors are calculated for each neuron by comparing apical and somatic activities. Notwithstanding, from a neuroscience perspective, it is not clear how a neuron could compare compartmental signals. Here, we propose a solution to this problem in that we let the apical feedback signal change the postsynaptic firing rate and combine this with a differential Hebbian update, a rate-based version of classical spiking time-dependent plasticity (STDP). We prove that weight updates of this form minimize two alternative loss functions that we prove to be equivalent to the error-based losses used in machine learning: the inference latency and the amount of top-down feedback necessary. Moreover, we show that the use of differential Hebbian updates works similarly well in other feedback-based deep learning frameworks such as Predictive Coding or Equilibrium Propagation. Finally, our work removes a key requirement of biologically plausible models for deep learning and proposes a learning mechanism that would explain how temporal Hebbian learning rules can implement supervised hierarchical learning.

The primary motor cortex (MOp) is an important site for motor skill learning. Interestingly, neurons in MOp possess reward-related activity, presumably to facilitate reward-based motor learning. While pyramidal neurons (PNs) and different subtypes of GABAergic inhibitory interneurons (INs) in MOp all undergo cell-type specific plastic changes during motor learning, the vasoactive intestinal peptide-expressing inhibitory interneurons (VIP-INs) in MOp have been shown to preferentially respond to reward and play a critical role in the early phases of motor learning by triggering local circuit plasticity. To understand how VIP-INs might integrate various streams of information, such as sensory, pre-motor, and reward-related inputs, to regulate local plasticity in MOp, we performed monosynaptic rabies tracing experiments and employed an automated cell counting pipeline to generate a comprehensive map of brain-wide inputs to VIP-INs in MOp. We then compared this input profile to the brain-wide inputs to somatostatin-expressing inhibitory interneurons (SST-INs) and parvalbumin-expressing inhibitory interneurons (PV-INs) in MOp. We found that while all cell types received major inputs from sensory, motor, and prefrontal cortical regions, as well as from various thalamic nuclei, VIP-INs received more inputs from the orbital frontal cortex (ORB) - a region associated with reinforcement learning and value predictions. Our findings provide insight on how the brain leverages microcircuit motifs by both integrating and partitioning different streams of long-range input to modulate local circuit activity and plasticity.

Neural circuits are reorganized with specificity during learning. Genetically-defined subgroups of inhibitory interneurons are thought to play distinct roles in learning, but heterogeneity within these subgroups has limited our understanding of the scope and nature of their specific contributions to learning. Here we reveal that the chandelier cell (ChC), an interneuron type that specializes in inhibiting the axon-initial segment (AIS) of pyramidal neurons, establishes cortical microcircuits for organizing neural coding through selective axo-axonic synaptic plasticity. We find that organized motor control is mediated by enhanced population coding of direction-tuned premotor neurons, whose tuning is refined through suppression of irrelevant neuronal activity. ChCs are required for learning-dependent refinements via providing selective inhibitory control over pyramidal neurons rather than global suppression. Quantitative analysis on structural plasticity of axo-axonic synapses revealed that ChCs redistributed inhibitory weights to individual pyramidal neurons during learning. These results demonstrate an adaptive logic of the inhibitory circuit motif responsible for organizing distributed neural representations. Thus, ChCs permit efficient cortical computation in a target cell specific manner, which highlights the significance of interneuron diversity.

Hebb postulated that, to store information in the brain, assemblies of excitatory neurons coding for a percept are bound together via associative long-term synaptic plasticity. In this view, it is unclear what role, if any, is carried out by inhibitory interneurons. Indeed, some have argued that inhibitory interneurons are not plastic. Yet numerous recent studies have demonstrated that, similar to excitatory neurons, inhibitory interneurons also undergo long-term plasticity. Here, we discuss the many diverse forms of long-term plasticity that are found at inputs to and outputs from several types of cortical inhibitory interneuron, including their plasticity of intrinsic excitability and their homeostatic plasticity. We explain key plasticity terminology, highlight key interneuron plasticity mechanisms, extract overarching principles and point out implications for healthy brain functionality as well as for neuropathology. We introduce the concept of the plasticitome - the synaptic plasticity counterpart to the genome or the connectome - as well as nomenclature and definitions for dealing with this rich diversity of plasticity. We argue that the great diversity of interneuron plasticity rules is best understood at the circuit level, for example as a way of elucidating how the credit-assignment problem is solved in deep biological neural networks.

Memories can be modified by new experience in a specific or generalized manner. Changes in synaptic connections are crucial for memory storage, but it remains unknown how synaptic changes associated with different memories are distributed within neuronal circuits and how such distributions affect specific or generalized modification by novel experience. Here we show that fear conditioning with two different auditory stimuli (CS) and footshocks (US) induces dendritic spine elimination mainly on different dendritic branches of layer 5 pyramidal neurons in the mouse motor cortex. Subsequent fear extinction causes CS-specific spine formation and extinction of freezing behavior. In contrast, spine elimination induced by fear conditioning with >2 different CS-USs often co-exists on the same dendritic branches. Fear extinction induces CS-nonspecific spine formation and generalized fear extinction. Moreover, activation of somatostatin-expressing interneurons increases the occurrence of spine elimination induced by different CS-USs on the same dendritic branches and facilitates the generalization of fear extinction. These findings suggest that specific or generalized modification of existing memories by new experience depends on whether synaptic changes induced by previous experiences are segregated or co-exist at the level of individual dendritic branches.

The SCN1A gene is strongly associated with epilepsy and plays a central role for supporting cortical excitation-inhibition balance through the expression of Na_V1.1 within inhibitory interneurons. The phenotype of SCN1A disorders has been conceptualized as driven primarily by impaired interneuron function that predisposes to disinhibition and cortical hyperexcitability. However, recent studies have identified SCN1A gain-of-function variants associated with epilepsy, and the presence of cellular and synaptic changes in mouse models that point toward homeostatic adaptations and complex network remodeling. These findings highlight the need to understand microcircuit-scale dysfunction in SCN1A disorders to contextualize genetic and cellular disease mechanisms. Targeting the restoration of microcircuit properties may be a fruitful strategy for the development of novel therapies.